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Traditional clinical research relies on conventional strategies to invite and enroll research participants. However, these strategies often fail to reach potential participants from marginalized communities or that reflect the diversity of the nation, such as race, ethnicity, or geography. As we discuss here, the digital clinical study model sets the stage for improved and equitable participation in biomedical research.

UNSTRUCTURED Electronic health record (EHR) technology has become a central digital health tool throughout health care. EHR systems are responsible for a growing number of vital functions for hospitals and providers. More recently, patient-facing EHR tools are allowing patients to interact with their EHR and connect external sources of health data, such as wearable fitness trackers, personal genomics, and outside health services, to it. As patients become more engaged with their EHR, the volume and variety of digital health information will serve an increasingly useful role in health care and health research. Particularly due to the COVID-19 pandemic, the ability for the biomedical research community to pivot to fully remote research, driven largely by EHR data capture and other digital health tools, is an exciting development that can significantly reduce burden on study participants, improve diversity in clinical research, and equip researchers with more robust clinical data. In this viewpoint, we describe how patient engagement with EHR technology is poised to advance the digital clinical trial space, an innovative research model that is uniquely accessible and inclusive for study participants.

Traditional viral illness surveillance relies on in-person clinical or laboratory data, paper-based data collection, and outdated technology for data transfer and aggregation. We aimed to assess whether continuous sensor data can provide an early warning signal for COVID-19 activity as individual physiological and behavioural changes might precede symptom onset, care seeking, and diagnostic testing.This multivariable, population-based, modelling study recruited adult (aged ≥18 years) participants living in the USA who had a smartwatch or fitness tracker on any device that connected to Apple HealthKit or Google Fit and had joined the DETECT study by downloading the MyDataHelps app. In the model development cohort, we included people who had participated in DETECT between April 1, 2020, and Jan 14, 2022. In the validation cohort, we included individuals who had participated between Jan 15 and Feb 15, 2022. When a participant joins DETECT, they fill out an intake survey of demographic information, including their ZIP code (postal code), and surveys on symptoms, symptom onset, and viral illness test dates and results, if they become unwell. When a participant connects their device, historical sensor data are collected, if available. Sensor data continue to be collected unless a participant withdraws from the study. Using sensor data, we collected each participant's daily resting heart rate and step count during the entire study period and identified anomalous sensor days, in which resting heart rate was higher than, and step count was lower than, a specified threshold calculated for each individual by use of their baseline data. The proportion of users with anomalous data each day was used to create a 7-day moving average. For the main cohort, a negative binomial model predicting 7-day moving averages for COVID-19 case counts, as reported by the Centers for Disease Control and Prevention (CDC), in real time, 6 days in the future, and 12 days in the future in the USA and California was fitted with CDC-reported data from 3 days before alone (Hsub0/sub) or in combination with anomalous sensor data (Hsub1/sub). We compared the predictions with Pearson correlation. We then validated the model in the validation cohort.Between April 1, 2020, and Jan 14, 2022, 35 842 participants enrolled in DETECT, of whom 4006 in California and 28 527 in the USA were included in our main cohort. The Hsub1/submodel significantly outperformed the Hsub0/submodel in predicting the 7-day moving average COVID-19 case counts in California and the USA. For example, Pearson correlation coefficients for predictions 12 days in the future increased by 32·9% in California (from 0·70 [95% CI 0·65-0·73] to 0·93 [0·92-0·94]) and by 12·2% (from 0·82 [0·79-0·84] to 0·92 [0·91-0·93]) in the USA from the Hsub0/submodel to the Hsub1/submodel. Our validation model also showed significant correlations for predictions in real time, 6 days in the future, and 12 days in the future.Our study showed that passively collected sensor data from consenting participants can provide real-time disease tracking and forecasting. With a growing population of wearable technology users, these sensor data could be integrated into viral surveillance programmes.The National Center for Advancing Translational Sciences of the US National Institutes of Health, The Rockefeller Foundation, and Amazon Web Services.

Background Viruses have high mutation rates and generally exist as a mixture of variants in biological samples. Next-generation sequencing (NGS) approaches have surpassed Sanger for generating long viral sequences, yet how variants affect NGS de novo assembly remains largely unexplored. Results Our results from > 15,000 simulated experiments showed that presence of variants can turn an assembly of one genome into tens to thousands of contigs. This “variant interference” (VI) is highly consistent and reproducible by ten commonly-used de novo assemblers, and occurs over a range of genome length, read length, and GC content. The main driver of VI is pairwise identities between viral variants. These findings were further supported by in silico simulations, where selective removal of minor variant reads from clinical datasets allow the “rescue” of full viral genomes from fragmented contigs. Conclusions These results call for careful interpretation of contigs and contig numbers from de novo assembly in viral deep sequencing.

Individual smartwatch or fitness band sensor data in the setting of COVID-19 has shown promise to identify symptomatic and pre-symptomatic infection or the need for hospitalization, correlations between peripheral temperature and self-reported fever, and an association between changes in heart-rate-variability and infection. In our study, a total of 38,911 individuals (61% female, 15% over 65) have been enrolled between March 25, 2020 and April 3, 2021, with 1,118 reported testing positive and 7,032 negative for COVID-19 by nasopharyngeal PCR swab test. We propose an explainable gradient boosting prediction model based on decision trees for the detection of COVID-19 infection that can adapt to the absence of self-reported symptoms and to the available sensor data, and that can explain the importance of each feature and the post-test-behavior for the individuals. We tested it in a cohort of symptomatic individuals who exhibited an AUC of 0.83 [0.81-0.85], or AUC=0.78 [0.75-0.80] when considering only data before the test date, outperforming state-of-the-art algorithm in these conditions. The analysis of all individuals (including asymptomatic and pre-symptomatic) when self-reported symptoms were excluded provided an AUC of 0.78 [0.76-0.79], or AUC of 0.70 [0.69-0.72] when considering only data before the test date. Extending the use of predictive algorithms for detection of COVID-19 infection based only on passively monitored data from any device, we showed that it is possible to scale up this platform and apply the algorithm in other settings where self-reported symptoms can not be collected.

Background Haemophilus influenzae (Hi) can cause invasive diseases such as meningitis, pneumonia, or sepsis. Typeable Hi includes six serotypes (a through f), each expressing a unique capsular polysaccharide. The capsule, encoded by the genes within the capsule locus, is a major virulence factor of typeable Hi. Non-typeable (NTHi) does not express capsule and is associated with invasive and non-invasive diseases. Methods A total of 395 typeable and 293 NTHi isolates were characterized by whole genome sequencing (WGS). Phylogenetic analysis and multilocus sequence typing were used to characterize the overall genetic diversity. Pair-wise comparisons were used to evaluate the capsule loci. A WGS serotyping method was developed to predict the Hi serotype. WGS serotyping results were compared to slide agglutination (SAST) or real-time PCR (rt-PCR) serotyping. Results Isolates of each Hi serotype clustered into one or two subclades, with each subclade being associated with a distinct sequence type (ST). NTHi isolates were genetically diverse, with seven subclades and 125 STs being detected. Regions I and III of the capsule locus were conserved among the six serotypes (≥82% nucleotide identity). In contrast, genes in Region II were less conserved, with only six gene pairs from all serotypes showing ≥56% nucleotide identity. The WGS serotyping method was 99.9% concordant with SAST and 100% concordant with rt-PCR in determining the Hi serotype. Conclusions Genomic analysis revealed a higher degree of genetic diversity among NTHi compared to typeable Hi. The WGS serotyping method accurately predicted the Hi capsule type and can serve as an alternative method for Hi serotyping.

Two mRNA vaccines and one adenovirus-based vaccine against SARS CoV-2 are currently being distributed at scale in the United States. Objective evidence of a specific individual’s physiologic response to that vaccine are not routinely tracked but may offer insights into the acute immune response and personal and/or vaccine characteristics associated with that. We explored this possibility using a smartphone app-based research platform developed early in the pandemic that enabled volunteers (38,911 individuals between 25 March 2020 and 4 April 2021) to share their smartwatch and activity tracker data, as well as self-report, when appropriate, any symptoms, COVID-19 test results and vaccination dates and type. Of 4,110 individuals who reported at least one mRNA vaccination dose, 3,312 provided adequate resting heart rate data from the peri-vaccine period for analysis. We found changes in resting heart rate with respect to an individual baseline increased the days after vaccination, peaked on day 2, and returned to normal on day 6, with a much stronger effect after second dose with respect to first dose (average changes 1.6 versus 0.5 beats per minute). The changes were more pronounced for individuals who received the Moderna vaccine (on both doses), those who previously tested positive to COVID-19 (on dose 1), and for individuals aged

Traditional screening for COVID-19 typically includes survey questions about symptoms, travel history, and sometimes temperature measurements. We explored whether longitudinal, personal sensor data can help identify subtle changes which may indicate an infection, such as COVID-19. To do this we developed an app that collects smartwatch and activity tracker data, as well as self-reported symptoms and diagnostic testing results from participants living in the US. We assessed whether symptoms and sensor data could differentiate COVID-19 positive versus negative cases in symptomatic individuals. Between March 25 and June 7, 2020, we enrolled 30,529 participants, of whom 3,811 reported symptoms, 54 reported testing positive for COVID-19, and 279 negative. We found that a combination of symptom and sensor data resulted in an AUC=0.80 [0.73 – 0.86] which was significantly better (p < 0.01) than a model which just considered symptoms alone (AUC=0.71 [0.63 – 0.79]) in the discrimination between symptomatic individuals positive or negative for COVID-19. Such orthogonal, continuous, passively captured data may be complementary to virus testing that is generally a one-off, or infrequent, sampling assay.

Traditional screening for COVID-19 typically includes survey questions about symptoms and travel history, as well as temperature measurements. Here, we explore whether personal sensor data collected over time may help identify subtle changes indicating an infection, such as in patients with COVID-19. We have developed a smartphone app that collects smartwatch and activity tracker data, as well as self-reported symptoms and diagnostic testing results, from individuals in the United States, and have assessed whether symptom and sensor data can differentiate COVID-19 positive versus negative cases in symptomatic individuals. We enrolled 30,529 participants between 25 March and 7 June 2020, of whom 3,811 reported symptoms. Of these symptomatic individuals, 54 reported testing positive and 279 negative for COVID-19. We found that a combination of symptom and sensor data resulted in an area under the curve (AUC) of 0.80 (interquartile range (IQR): 0.73-0.86) for discriminating between symptomatic individuals who were positive or negative for COVID-19, a performance that is significantly better (P < 0.01) than a model1 that considers symptoms alone (AUC = 0.71; IQR: 0.63-0.79). Such continuous, passively captured data may be complementary to virus testing, which is generally a one-off or infrequent sampling assay.

This cohort study examines the duration and variation of recovery among COVID-19–positive verses COVID-19–negative individuals.

Invasive meningococcal disease is mainly caused by Neisseria meningitidis serogroups A, B, C, X, W, and Y. The serogroup is typically determined by slide agglutination serogrouping (SASG) and real-time PCR (RT-PCR). We describe a whole-genome sequencing (WGS)-based method to characterize the capsule polysaccharide synthesis (cps) locus, classify N. meningitidis serogroups, and identify mechanisms for nongroupability using 453 isolates from a global strain collection. We identified novel genomic organizations within functional cps loci, consisting of insertion sequence (IS) elements in unique positions that did not disrupt the coding sequence. Genetic mutations (partial gene deletion, missing genes, IS insertion, internal stop, and phase-variable off) that led to nongroupability were identified. The results of WGS and SASG were in 91% to 100% agreement for all serogroups, while the results of WGS and RT-PCR showed 99% to 100% agreement. Among isolates determined to be nongroupable by WGS (31 of 453), the results of all three methods agreed 100% for those without a capsule polymerase gene. However, 61% (WGS versus SASG) and 36% (WGS versus RT-PCR) agreements were observed for the isolates, particularly those with phase variations or internal stops in cps loci, which warrant further characterization by additional tests. Our WGS-based serogrouping method provides comprehensive characterization of the N. meningitidis capsule, which is critical for meningococcal surveillance and outbreak investigations.

Next-generation sequencing (NGS) has become a vital tool in clinical microbiology, with numerous applications in infectious disease diagnostics, outbreak investigations, and public health surveillance. Although the NGS technology enables comprehensive pathogen detection in a relatively short time at a low cost, the enormous amount of genomics data generated creates a critical challenge of effectively organizing, archiving, analyzing, and reporting the results within a clinically relevant timeframe. Automated pipelines provide the first step in standardizing NGS data processing and reporting, thus eliminating the common bottlenecks in bioinformatics analyses, and providing rapid turnaround. Here, we present the Viral NGS Pipeline optimized for identification and whole genome assembly of viruses, and the Bacterial Meningococcus Genome Analysis Platform (BMGAP), designed for genotypic characterization of meningitis pathogens. These respective pipelines have been used to analyze more than 11,000 clinical samples and isolates. The pipelines are deployable on both standalone and cloud-based servers, enabling their accessibility to internal CDC users, as well as external partners, including state public health laboratories and other collaborators worldwide. These automated pipelines have the potential to contribute to the development of unbiased NGS-based clinical assays for pathogen detection that demand rapid turnaround times, and are expected to play a key role in infectious disease surveillance in the future.

In Drosophila, dosage compensation is mediated by the MSL complex, which binds numerous sites on the X chromosome in males and enhances the transcriptional rate of a substantial number of X-linked genes. We have determined that topoisomerase II (Topo II) is enriched on dosage compensated genes, to which it is recruited by association with the MSL complex, in excess of the amount that is present on autosomal genes with similar transcription levels. Using a plasmid model, we show that Topo II is required for proper dosage compensation and that compensated chromatin is topologically different from non-compensated chromatin. This difference, which is not the result of the enhanced transcription level due of X-linked genes and which represents a structural modification intrinsic to the DNA of compensated chromatin, requires the function of Topo II. Our results suggest that Topo II is an integral part of the mechanistic basis of dosage compensation.

Brd4 is a double bromodomain protein that has been shown to interact with acetylated histones to regulate transcription by recruiting Positive Transcription Elongation Factor b to the promoter region. Brd4 is also involved in gene bookmarking during mitosis and is a therapeutic target for the treatment of acute myeloid leukemia. The Drosophila melanogaster Brd4 homologue is called Fs(1)h and, like its vertebrate counterpart, encodes different isoforms. We have used ChIP-seq to examine the genome-wide distribution of Fs(1)h isoforms. We are able to distinguish the Fs(1)h-L and Fs(1)h-S binding profiles and discriminate between the genomic locations of the two isoforms. Fs(1)h-S is present at enhancers and promoters and its amount parallels transcription levels. Correlations between the distribution of Fs(1)h-S and various forms of acetylated histones H3 and H4 suggest a preference for binding to H3K9acS10ph. Surprisingly, Fs(1)h-L is located at sites in the genome where multiple insulator proteins are also present. The results suggest that Fs(1)h-S may be responsible for the classical role assigned to this protein, whereas Fs(1)h-L may have a new and unexpected role in chromatin architecture by working in conjunction with insulator proteins to mediate intra- or inter-chromosome interactions.

The poliovirus (PV) is currently targeted for worldwide eradication and containment. Sanger-based sequencing of the viral protein 1 (VP1) capsid region is currently the standard method for PV surveillance. However, the whole-genome sequence is sometimes needed for higher resolution global surveillance. In this study, we optimized whole-genome sequencing protocols for poliovirus isolates and FTA cards using next-generation sequencing (NGS), aiming for high sequence coverage, efficiency, and throughput. We found that DNase treatment of poliovirus RNA followed by random reverse transcription (RT), amplification, and the use of the Nextera XT DNA library preparation kit produced significantly better results than other preparations. The average viral reads per total reads, a measurement of efficiency, was as high as 84.2% ± 15.6%. PV genomes covering >99 to 100% of the reference length were obtained and validated with Sanger sequencing. A total of 52 PV genomes were generated, multiplexing as many as 64 samples in a single Illumina MiSeq run. This high-throughput, sequence-independent NGS approach facilitated the detection of a diverse range of PVs, especially for those in vaccine-derived polioviruses (VDPV), circulating VDPV, or immunodeficiency-related VDPV. In contrast to results from previous studies on other viruses, our results showed that filtration and nuclease treatment did not discernibly increase the sequencing efficiency of PV isolates. However, DNase treatment after nucleic acid extraction to remove host DNA significantly improved the sequencing results. This NGS method has been successfully implemented to generate PV genomes for molecular epidemiology of the most recent PV isolates. Additionally, the ability to obtain full PV genomes from FTA cards will aid in facilitating global poliovirus surveillance.

The rapid advancement from single-gene testing to whole genome sequencing has significantly broadened the type and amount of information available to researchers, physicians, patients, and the public in general. Much debate has ensued about whether genomic test results should be reported to research participants, patients and consumers, and at what stage we can be sure that existing evidence justifies their use in clinical settings. Courts and judges evaluating the utility of these results will not be immune to this uncertainty. As scholars increasingly explore the duty of care standards related to reporting genomic test results, it is timely to provide a framework for understanding how uncertainty about genetic and genomic tests influences evidentiary considerations in the court room. Here, we explore the subtleties and nuances of interpreting genetic data in an environment of substantial discord related to the value that individuals should place on genetic and genomic tests. In conjunction, we discuss the roles courts should play in qualifying experts, expert testimony, and genetic and genomic tests given the intricate and complex nature of genetic and genomic information.

Genomic science and associated technologies are providing scientists and clinicians with novel insights that are transforming the delivery of healthcare and the overall well-being of society. However, these insights inform us that historical population sampling approaches for investigating rare and common genetic variations are not representative of the complex ancestral backgrounds of today’s patients. In order for personalized medicine to be meaningful and applicable to the global populations, we will need to know how common and rare genetic variants found in different parts of the world influence health and drug response. This article demonstrates the importance of increasing ethnic and racial diversity among participants in genomic research, highlights areas of opportunity for improving our understanding of genomic diversity among populations, and provides examples of successful models that help to resolve these concerns.

Understanding the relationship between genome organization and expression is central to understanding genome function. Closely apposed genes in a head-to-head orientation share the same upstream region and are likely to be coregulated. Here we identify the Drosophila BEAF-32 insulator as a cis regulatory element separating close head-to-head genes with different transcription regulation modes. We then compare the binding landscapes of the BEAF-32 insulator protein in four different Drosophila genomes and highlight the evolutionarily conserved presence of this protein between close adjacent genes. We find that changes in binding of BEAF-32 to sites in the genome of different Drosophila species correlate with alterations in genome organization caused by DNA rearrangements or genome size expansion. The cross-talk between BEAF-32 genomic distribution and genome organization contributes to new gene-expression profiles, which in turn translate into specific and distinct phenotypes. The results suggest a mechanism for the establishment of differences in transcription patterns during evolution.

Several multiprotein DNA complexes capable of insulator activity have been identified in Drosophila melanogaster, yet only CTCF, a highly conserved zinc finger protein, and the transcription factor TFIIIC have been shown to function in mammals. CTCF is involved in diverse nuclear activities, and recent studies suggest that the proteins with which it associates and the DNA sequences that it targets may underlie these various roles. Here we show that the Drosophila homolog of CTCF (dCTCF) aligns in the genome with other Drosophila insulator proteins such as Suppressor of Hairy wing [SU(HW)] and Boundary Element Associated Factor of 32 kDa (BEAF-32) at the borders of H3K27me3 domains, which are also enriched for associated insulator proteins and additional cofactors. RNAi depletion of dCTCF and combinatorial knockdown of gene expression for other Drosophila insulator proteins leads to a reduction in H3K27me3 levels within repressed domains, suggesting that insulators are important for the maintenance of appropriate repressive chromatin structure in Polycomb (Pc) domains. These results shed new insights into the roles of insulators in chromatin domain organization and support recent models suggesting that insulators underlie interactions important for Pc-mediated repression. We reveal an important relationship between dCTCF and other Drosophila insulator proteins and speculate that vertebrate CTCF may also align with other nuclear proteins to accomplish similar functions.

Transcription regulation is mediated by enhancers that bind sequence-specific transcription factors, which in turn interact with the promoters of the genes they control. Here, we show that the JIL-1 kinase is present at both enhancers and promoters of ecdysone-induced Drosophila genes, where it phosphorylates the Ser10 and Ser28 residues of histone H3. JIL-1 is also required for CREB binding protein (CBP)-mediated acetylation of Lys27, a well-characterized mark of active enhancers. The presence of these proteins at enhancers and promoters of ecdysone-induced genes results in the establishment of the H3K9acS10ph and H3K27acS28ph marks at both regulatory sequences. These modifications are necessary for the recruitment of 14-3-3, a scaffolding protein capable of facilitating interactions between two simultaneously bound proteins. Chromatin conformation capture assays indicate that interaction between the enhancer and the promoter is dependent on the presence of JIL-1, 14-3-3, and CBP. Genome-wide analyses extend these conclusions to most Drosophila genes, showing that the presence of JIL-1, H3K9acS10ph, and H3K27acS28ph is a general feature of enhancers and promoters in this organism.

Total serum bilirubin is associated with several clinical outcomes, including cardiovascular disease, diabetes and drug metabolism. We conducted a genome-wide association study in 619 healthy unrelated African Americans in an attempt to replicate reported findings in Europeans and Asians and to identify novel loci influencing total serum bilirubin levels. We analyzed a dense panel of over two million genotyped and imputed SNPs in additive genetic models adjusting for age, sex, and the first two significant principal components from the sample covariance matrix of genotypes. Thirty-nine SNPs spanning a 78 kb region within the UGT1A1 displayed P-values5 × 10(-8). The lowest P-value was 1.7 × 10(-22) for SNP rs887829. None of SNPs in the UGT1A1 remained statistically significant in conditional association analyses that adjusted for rs887829. In addition, SNP rs10929302 located in phenobarbital response enhancer module was significantly associated with bilirubin level with a P-value of 1.37 × 10(-11); this enhancer module is believed to have a critical role in phenobarbital treatment of hyperbilirubinemia. Interestingly, the lead SNP, rs887829, is in strong linkage disequilibrium (LD) (r(2)≥0.74) with rs10929302. Taking advantage of the lower LD and shorter haplotypes in African-ancestry populations, we identified rs887829 as a more refined proxy for the causative variant influencing bilirubin levels. Also, we replicated the reported association between variants in SEMA3C and bilirubin levels. In summary, UGT1A1 is a major locus influencing bilirubin levels and the results of this study promise to contribute to understanding of the etiology and treatment of hyperbilirubinaemia in African-ancestry populations.

Insulators are multi-protein-DNA complexes thought to affect gene expression by mediating inter- and intra-chromosomal interactions. Drosophila insulators contain specific DNA binding proteins plus common components, such as CP190, that facilitate these interactions. Here we examine changes in the distribution of Drosophila insulator proteins during the heat-shock and ecdysone responses. We find that CP190 recruitment to insulator sites is the main regulatable step in controlling insulator function during heat shock. In contrast, both CP190 and DNA binding protein recruitment are regulated during the ecdysone response. CP190 is necessary to stabilize specific chromatin loops and for proper activation of transcription of genes regulated by this hormone. These findings suggest that cells may regulate recruitment of insulator proteins to the DNA in order to activate insulator activity at specific sites and create distinct patterns of nuclear organization that are necessary to achieve proper gene expression in response to different stimuli.

Aims/hypothesis Chronically elevated blood glucose (hyperglycaemia) is the primary indicator of type 2 diabetes, which has a prevalence that varies considerably by ethnicity in the USA, with African-Americans disproportionately affected. Genome-wide association studies (GWASs) have significantly enhanced our understanding of the genetic basis of diabetes and related traits, including fasting plasma glucose (FPG). However, the majority of GWASs have been conducted in populations of European ancestry. Thus, it is important to conduct replication analyses in populations with non-European ancestry to identify shared loci associated with FPG across populations. Methods We used data collected from non-diabetic unrelated African-American individuals (n = 927) who participated in the Howard University Family Study to attempt to replicate previously published GWASs of FPG. Of the 29 single nucleotide polymorphisms (SNPs) previously reported, we directly tested 20 in this study. In addition to the direct test, we queried a 500 kb window centred on all 29 reported SNPs for local replication of additional markers in linkage disequilibrium (LD). Results Using direct SNP and LD-based comparisons, we replicated multiple SNPs previously associated with FPG and strongly associated with type 2 diabetes in populations with European ancestry. The replicated SNPs included those in or near TCF7L2, SLC30A8, G6PC2, MTNR1B, DGKB-TMEM195 and GCKR. We also replicated additional variants in LD with the reported SNPs in ZMAT4 and adjacent to IRS1. Conclusions/interpretation We identified multiple GWAS variants for FPG in our cohort of African-Americans. Using an LD-based strategy we also identified SNPs not previously reported, demonstrating the utility of using diverse populations for replication analysis. Electronic supplementary material The online version of this article (doi:10.1007/s00125-010-2002-7) contains supplementary material, which is available to authorised users.

Background Benign ethnic neutropenia (BEN) is a hematologic condition associated with people of African ancestry and specific Middle Eastern ethnic groups. Prior genetic association studies in large population showed that rs2814778 in Duffy Antigen Receptor for Chemokines (DARC) gene, specifically DARC null red cell phenotype, was associated with BEN. However, the mechanism of this red cell phenotype leading to low white cell count remained elusive. Methods We conducted an extreme phenotype design genome-wide association study (GWAS), analyzed ~16 million single nucleotide polymorphisms (SNP) in 1,178 African-Americans individuals from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study and replicated from 819 African-American participants in the Atherosclerosis Risk in Communities (ARIC) study. Conditional analyses on rs2814778 were performed to identify additional association signals on chromosome 1q22. In a separate cohort of healthy individuals with and without BEN, whole genome gene expression from peripheral blood neutrophils were analyzed for DARC. Results We confirmed that rs2814778 in DARC was associated with BEN (p = 4.09×10-53). Conditioning on rs2814778 abolished other significant chromosome 1 associations. Inflammatory cytokines (IL-2, 6, and 10) in participants in the Howard University Family Study (HUFS) and Multi-Ethnic Study in Atherosclerosis (MESA) showed similar levels in individuals homozygous for the rs2814778 allele compared to others, indicating cytokine sink hypothesis played a minor role in leukocyte homeostasis. Gene expression in neutrophils of individuals with and without BEN was also similar except for low DARC expression in BEN, suggesting normal function. BEN neutrophils had slightly activated profiles in leukocyte migration and hematopoietic stem cell mobilization pathways (expression fold change Conclusions These results in humans support the notion of DARC null erythroid progenitors preferentially differentiating to myeloid cells, leading to activated DARC null neutrophils egressing from circulation to the spleen, and causing relative neutropenia. Collectively, these human data sufficiently explained the mechanism DARC null red cell phenotype causing BEN and further provided a biologic basis that BEN is clinically benign.

Chromatin insulators have been implicated in the regulation of higher-order chromatin structure and may function to compartmentalize the eukaryotic genome into independent domains of gene expression. To test this possibility, we used biochemical and computational approaches to identify gypsy-like genomic-binding sites for the Suppressor of Hairy-wing [Su(Hw)] protein, a component of the gypsy insulator. EMSA and FISH analyses suggest that these are genuine Su(Hw)-binding sites. In addition, functional tests indicate that genomic Su(Hw)-binding sites can inhibit enhancer–promoter interactions and thus function as bona fide insulators. The insulator strength is dependent on the genomic location of the transgene and the number of Su(Hw)-binding sites, with clusters of two to three sites showing a stronger effect than individual sites. These clusters of Su(Hw)-binding sites are located mostly in intergenic regions or in introns of large genes, an arrangement that fits well with their proposed role in the formation of chromatin domains. Taken together, these data suggest that genomic gypsy-like insulators may provide a means for the compartmentalization of the genome within the nucleus.

SummaryAppropriate cell number and organ size in a multicellular organism are determined by coordinated cell growth, proliferation, and apoptosis. Disruption of these processes can cause cancer. Recent studies have identified the Large tumor suppressor (Lats)/Warts (Wts) protein kinase as a key component of a pathway that controls the coordination between cell proliferation and apoptosis. Here we describe growth inhibitory functions for a Mob superfamily protein, termed Mats (Mob as tumor suppressor), in Drosophila. Loss of Mats function results in increased cell proliferation, defective apoptosis, and induction of tissue overgrowth. We show that mats and wts function in a common pathway. Mats physically associates with Wts to stimulate the catalytic activity of the Wts kinase. A human Mats ortholog (Mats1) can rescue the lethality associated with loss of Mats function in Drosophila. As Mats1 is mutated in human tumors, Mats-mediated growth inhibition and tumor suppression is likely conserved in humans.

Receptor tyrosine kinase (RTK) signaling plays an instructive role in cell fate decisions, whereas Notch signaling is often involved in restricting cellular competence for differentiation. Genetic interactions between these two evolutionarily conserved pathways have been extensively documented. The underlying molecular mechanisms, however, are not well understood. Here, we show that Yan, an Ets transcriptional repressor that blocks cellular potential for specification and differentiation [1, 2], is a target of Notch signaling during Drosophila eye development. The Suppressor of Hairless (Su[H]) protein of the Notch pathway is required for activating yan expression, and Su(H) binds directly to an eye-specific yan enhancer in vitro. In contrast, yan expression is repressed by Pointed (Pnt), which is a key component of the RTK pathway. Pnt binds specifically to the yan enhancer and competes with Su(H) for DNA binding. This competition illustrates a potential mechanism for RTK and Notch signals to oppose each other. Thus, yan serves as a common target of Notch/Su(H) and RTK/Pointed signaling pathways during cell fate specification.

Background Strains from a collection of Drosophila GFP protein trap lines express GFP in the normal tissues where the endogenous protein is present. This collection can be used to screen for proteins distributed in the nucleus in a non-uniform pattern. Methodology/Principal Findings We analyzed four lines that show peripheral or punctate nuclear staining. One of these lines affects an uncharacterized gene named CG11138. The CG11138 protein shows a punctate distribution in the nuclear periphery similar to that of Drosophila insulator proteins but does not co-localize with known insulators. Interestingly, mutations in Lamin proteins result in alterations in CG11138 localization, suggesting that this protein may be a novel component of the nuclear lamina. A second line affects the Decondensation factor 31 (Df31) gene, which encodes a protein with a unique nuclear distribution that appears to segment the nucleus into four different compartments. The X-chromosome of males is confined to one of these compartments. We also find that Drosophila Nucleoplasmin (dNlp) is present in regions of active transcription. Heat shock leads to loss of dNlp from previously transcribed regions of polytene chromosome without redistribution to the heat shock genes. Analysis of Stonewall (Stwl), a protein previously found to be necessary for the maintenance of germline stem cells, shows that Stwl is present in a punctate pattern in the nucleus that partially overlaps with that of known insulator proteins. Finally we show that Stwl, dNlp, and Df31 form part of a highly interactive network. The properties of other components of this network may help understand the role of these proteins in nuclear biology. Conclusions/Significance These results establish screening of GFP protein trap alleles as a strategy to identify factors with novel cellular functions. Information gained from the analysis of CG11138 Stwl, dNlp, and Df31 sets the stage for future studies of these proteins.

Insulin resistance (IR) is a key determinant of type 2 diabetes (T2D) and other metabolic disorders. This genome-wide association study (GWAS) was designed to shed light on the genetic basis of fasting insulin (FI) and IR in 927 non-diabetic African Americans. 5 396 838 single-nucleotide polymorphisms (SNPs) were tested for associations with FI or IR with adjustments for age, sex, body mass index, hypertension status and first two principal components. Genotyped SNPs (n = 12) with P5 × 10(-6) in African Americans were carried forward for de novo genotyping in 570 non-diabetic West Africans. We replicated SNPs in or near SC4MOL and TCERG1L in West Africans. The meta-analysis of 1497 African Americans and West Africans yielded genome-wide significant associations for SNPs in the SC4MOL gene: rs17046216 (P = 1.7 × 10(-8) and 2.9 × 10(-8) for FI and IR, respectively); and near the TCERG1L gene with rs7077836 as the top scoring (P = 7.5 × 10(-9) and 4.9 × 10(-10) for FI and IR, respectively). In silico replication in the MAGIC study (n = 37 037) showed weak but significant association (adjusted P-value of 0.0097) for rs34602777 in the MYO5A gene. In addition, we replicated previous GWAS findings for IR and FI in Europeans for GCKR, and for variants in four T2D loci (FTO, IRS1, KLF14 and PPARG) which exert their action via IR. In summary, variants in/near SC4MOL, and TCERG1L were associated with FI and IR in this cohort of African Americans and were replicated in West Africans. SC4MOL is under-expressed in an animal model of T2D and plays a key role in lipid biosynthesis, with implications for the regulation of energy metabolism, obesity and dyslipidemia. TCERG1L is associated with plasma adiponectin, a key modulator of obesity, inflammation, IR and diabetes.

Recent developments in high-throughput genotyping and whole-genome sequencing will enhance the identification of disease loci in admixed populations. We discuss how a more refined estimation of ancestry benefits both admixture mapping and association mapping, making disease loci identification in admixed populations more powerful. High-throughput genotyping and sequencing will enable refined estimation of ancestry, thus enhancing disease loci identification in admixed populations

Insulators are DNA sequences thought to be important for the establishment and maintenance of cell-type specific nuclear architecture. In Drosophila there are several classes of insulators that appear to have unique roles in gene expression. The mechanisms involved in determining and regulating the specific roles of these insulator classes are not understood. Here we report that DNA Topoisomerase II modulates the activity of the Su(Hw) insulator. Downregulation of Topo II by RNAi or mutations in the Top2 gene result in disruption of Su(Hw) insulator function. This effect is mediated by the Mod(mdg4)2.2 protein, which is a unique component of the Su(Hw) insulator complex. Co-immunoprecipitation and yeast two-hybrid experiments show that Topo II and Mod(mdg4)2.2 proteins directly interact. In addition, mutations in Top2 cause a slight decrease of Mod(mdg4)2.2 transcript but have a dramatic effect on Mod(mdg4)2.2 protein levels. In the presence of proteasome inhibitors, normal levels of Mod(mdg4)2.2 protein and its binding to polytene chromosomes are restored. Thus, Topo II is required to prevent Mod(mdg4)2.2 degradation and, consequently, to stabilize Su(Hw) insulator-mediated chromatin organization.

Background The study of human genetic variation has been advanced by research such as genome-wide association studies, which aim to identify variants associated with common, complex diseases and traits. Significant strides have already been made in gleaning information on susceptibility, treatment, and prevention of a number of disorders. However, as genetic researchers continue to uncover underlying differences between individuals, there is growing concern that observed population-level differences will be inappropriately generalized as inherent to particular racial or ethnic groups and potentially perpetuate negative stereotypes. Discussion We caution that imprecision of language when conveying research conclusions, compounded by the potential distortion of findings by the media, can lead to the stigmatization of racial and ethnic groups. Summary It is essential that the scientific community and with those reporting and disseminating research findings continue to foster a socially responsible dialogue about genetic variation and human difference.

Insulators are protein-bound DNA elements that are thought to play a role in chromatin organization and the regulation of gene expression by mediating intra- and interchromosomal interactions. Suppressor of Hair-wing [Su(Hw)] and Drosophila CTCF (dCTCF) insulators are found at distinct loci throughout the Drosophila melanogaster genome and function by recruiting an additional protein, Centrosomal Protein 190 (CP190). We performed chromatin immunoprecipitation (ChIP) and microarray analysis (ChIP–chip) experiments with whole-genome tiling arrays to compare Su(Hw), dCTCF, boundary element-associated factor (BEAF), and CP190 localization on DNA in two different cell lines and found evidence that BEAF is a third subclass of CP190-containing insulators. The DNA-binding proteins Su(Hw), dCTCF, and BEAF show unique distribution patterns with respect to the location and expression level of genes, suggesting diverse roles for these three subclasses of insulators in genome organization. Notably, cell line-specific localization sites for all three DNA-binding proteins as well as CP190 indicate multiple levels at which insulators can be regulated to affect gene expression. These findings suggest a model in which insulator subclasses may have distinct functions that together organize the genome in a cell type-specific manner, resulting in differential regulation of gene expression.

Background DNA methylation is a major epigenetic modification important for regulating gene expression and suppressing spurious transcription. Most methods to scan the genome in different tissues for differentially methylated sites have focused on the methylation of CpGs in CpG islands, which are concentrations of CpGs often associated with gene promoters. Results Here, we use a methylation profiling strategy that is predominantly responsive to methylation differences outside of CpG islands. The method compares the yield from two samples of size-selected fragments generated by a methylation-sensitive restriction enzyme. We then profile nine different normal tissues from two human donors relative to spleen using a custom array of genomic clones covering the euchromatic portion of human chromosome 1 and representing 8% of the human genome. We observe gross regional differences in methylation states across chromosome 1 between tissues from the same individual, with the most striking differences detected in the comparison of cerebellum and spleen. Profiles of the same tissue from different donors are strikingly similar, as are the profiles of different lobes of the brain. Comparing our results with published gene expression levels, we find that clones exhibiting extreme ratios reflecting low relative methylation are statistically enriched for genes with high expression ratios, and vice versa, in most pairs of tissues examined. Conclusion The varied patterns of methylation differences detected between tissues by our methylation profiling method reinforce the potential functional significance of regional differences in methylation levels outside of CpG islands.

Yan is a nuclear DNA-binding protein that acts as a general inhibitor of cellular differentiation and proliferation in Drosophila melanogaster. The genetic and biochemical mechanisms required for regulating Yan protein function are well understood, however, the molecular mechanism of yan gene transcriptional regulation has not been fully elucidated. Here we show that the dynamic expression of the yan gene is specified by distinct spatial and temporal cis-acting regulatory elements in embryos and larval tissues. Each of these distinct elements is thus capable of replicating vital aspects of endogenous yan gene expression.

In order to eliminate health disparities in the United States, more efforts are needed to address the breadth of social issues directly contributing to the healthy divide observed across racial and ethnic groups. Socioeconomic status, education, and the environment are intimately linked to health outcomes. However, with the tremendous advances in technology and increased investigation into human genetic variation, genomics is poised to play a valuable role in bolstering efforts to find new treatments and preventions for chronic conditions and diseases that disparately affect certain ethnic groups. Promising studies focused on understanding the genetic underpinnings of diseases such as prostate cancer or beta-blocker treatments for heart failure are illustrative of the positive contribution that genomics can have on improving minority health.